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Psychological Foundations: Modeling Emotion
Research into human psychology has produced various models of emotion. This article summarizes the two models of emotion that contribute to the internal design of NeoThymos today.
The NeoThymos system is grounded in four categories of psychological model -
| Category | Model Represents… |
|---|---|
| cognitive appraisal theory | emotional responses to stimuli |
| emotional state models | continuous affective internal states |
| personality psychology | structure of individual differences |
| models of moral judgement | moral cognition, standards and norms |
Modeling Emotion
Psychological research has produced two specific models of human emotion that inspire the design of NeoThymos; the OCC model of cognitive appraisal theory and the PAD emotional state model. While these models are most often used to represent dynamic aspects of emotion they are used in the current static system to support the synthesis of more complete and realistic personality profiles for NeoThymos personas. Looking forward we anticipate new products and services intended to enable the cognitive appraisal of events and actions that will support a dynamic, homeostatic representation of emotion.
OCC - The Ortony, Clore and Collins Model of Emotion
The OCC model of emotion, developed by Andrew Ortony of Northwestern University, Gerald Clore of University of Virginia, and Allan Collins of Northwestern University, is a highly influential cognitive appraisal theory that provides a structured framework for understanding how emotions are generated. The model posits that emotions arise from how individuals cognitively appraise situations in three distinct ways: as events relative to personal goals (producing joy or distress), as actions of agents relative to standards (producing pride or shame), or as objects relative to attitudes (producing love or hate).
Because the model specifies 22 distinct emotion categories with clear, rule-based mechanisms, it has been foundational in artificial intelligence for programming emotionally responsive agents. The systematic, computational approach detailed in their seminal 1988 work The Cognitive Structure of Emotions made it particularly valuable for bridging psychology and computer science. In 2022, more than 30 years after its initial publication, the authors published a major second edition that refines and updates the OCC model, incorporating recent advances in emotion theory and affective computing, and includes a contributed chapter by Jonathan Gratch and Stacy Marsella describing the model’s profound influence on computational emotion modeling. Cambridge University PressResearchGate.
The PAD Emotional State Model
While the OCC model provides a taxonomy for appraising events, there is a need for a continuous substrate to represent the resulting emotional state. To achieve this, the system takes inspiration from the PAD (Pleasure-Arousal-Dominance) emotional state model, developed by Albert Mehrabian and James A. Russell (1974). Unlike categorical models that treat emotions as distinct islands (e.g., “Joy” vs. “Sadness”), PAD posits that all affective states can be mapped as coordinates within a multi-dimensional vector space.
The Three Dimensions of PAD:
The PAD model defines emotional experience along three orthogonal axes:
Pleasure (Valence): The qualitative evaluation of the state, ranging from negative (unpleasant) to positive (pleasant).
Arousal (Activation): The level of physical and mental energy associated with the state, ranging from low (sleepy/calm) to high (excited/alert).
Dominance (Control): The individual’s perceived level of control over the stimulus or situation, ranging from submissive (controlled by the environment) to dominant (in control of the environment).
Dominance is an important dimension. For example, emotions like Fear and Anger are both unpleasant and highly aroused; they are distinguished primarily by Dominance. Fear is characterized by low dominance (feeling threatened or overwhelmed), whereas Anger is characterized by high dominance (feeling an urge to attack or correct).
PAD representations can help serve as the mathematical “glue” between symbolic appraisals and neural representations. Because this approach casts emotion in a continuous space, it allows for the calculation of smooth emotional transitions, decay rates, and intensity blending.